The primary conventional method used for auditing transactional activity and detecting transactional fraud in retail loss prevention today is data mining of POS data (as typified by U.S. Pat. No. 5,895,453, the contents of which is hereby incorporated by reference), also referred to as “exception reporting”. In retail environments, this method relies on post-analysis of POS transaction data to identify trends and anomalies including those that may highlight fraudulent activity.
Other conventional systems include human monitoring systems and video monitoring systems that involve the use of loss prevention personnel overseeing a real-time video feed (or pre-recorded) to identify fraudulent transactions. This is most often done for sporadic spot checks basis or for investigations to find evidence to confirm or deny inferences from exception reporting.